cient Coding Schemes for the Hard Square Model

The hard square model consists of all binary arrays in which the s are isolated both hor izontally and vertically Based on a certain proba bility measure de ned on those arrays an e cient variable to xed rate encoder scheme is obtained that maps unconstrained binary words into arrays that sat isfy the hard square model For su ciently large ar rays the average rate of the encoder approaches a value which is only below the capacity of the constraint A second xed rate encoder is obtained whose rate for large arrays is within of the ca pacity value